{"id":"W4300649599","doi":"10.21203/rs.3.rs-1927294/v1","title":"Molecular formula discovery via bottom-up MS/MS interrogation","year":2022,"lang":"en","type":"preprint","venue":"Research Square","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia","keywords":"Interrogation; Computational biology; Computer science; Geography; Biology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007195735,0.001641012,0.0008695815,0.0023358,0.0005790129,0.002089418,0.001550092,0.001111761,0.007850751],"category_scores_gemma":[0.0023317,0.0006137433,0.000825438,0.001200712,0.000581704,0.002208662,0.002298326,0.002297971,0.00428955],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005684824,"about_ca_system_score_gemma":0.0006484555,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007723505,"about_ca_topic_score_gemma":0.001463872,"domain_scores_codex":[0.9992625,0.00005537936,0.00002912349,0.0001603459,0.00039374,0.00009900214],"domain_scores_gemma":[0.9991602,0.0002304339,0.0001114966,0.0002483921,0.0002021182,0.00004740782],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0005717835,0.0001460914,0.002202137,0.0003785105,0.0001922278,0.0005227081,0.0001044192,0.002261016,0.8649692,0.004861841,0.005728356,0.1180618],"study_design_scores_gemma":[0.00003357706,0.0001484724,0.001348542,0.00003294279,0.00008848343,0.0005959389,0.00007286532,0.03784946,0.9362968,0.007775004,0.01569913,0.00005872441],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.3868214,0.004658432,0.5520589,0.002452362,0.0008211039,0.0004933847,0.009383379,0.01390289,0.02940809],"genre_scores_gemma":[0.7056001,0.005310903,0.2635895,0.001300198,0.0002884505,0.0003245354,0.005972556,0.00159358,0.01602021],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.007850751,"threshold_uncertainty_score":0.02626336,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03113146652755257,"score_gpt":0.3643335475351313,"score_spread":0.3332020810075788,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}